What Weights Work for You? Adapting Weights for Any Pareto Front Shape in Decomposition-Based Evolutionary Multiobjective Optimisation

The quality of solution sets generated by decomposition-based evolutionary multi-objective optimisation (EMO) algorithms depends heavily on the consistency between a given problem's Pareto front shape and the specified weights' distribution. A set of weights distributed uniformly in a simp...

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Veröffentlicht in:Evolutionary computation Jg. 28; H. 2; S. 227
Hauptverfasser: Li, Miqing, Yao, Xin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 01.06.2020
Schlagworte:
Algorithms
Biological Evolution
Computer Simulation
many-objective optimisation
decomposition-based EMO
weight adaptation
Multiobjective optimisation
evolutionary algorithms
ISSN:1530-9304, 1530-9304
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Zusammenfassung:The quality of solution sets generated by decomposition-based evolutionary multi-objective optimisation (EMO) algorithms depends heavily on the consistency between a given problem's Pareto front shape and the specified weights' distribution. A set of weights distributed uniformly in a simplex often leads to a set of well-distributed solutions on a Pareto front with a simplex-like shape, but may fail on other Pareto front shapes. It is an open problem on how to specify a set of appropriate weights without the information of the problem's Pareto front beforehand. In this article, we propose an approach to adapt weights during the evolutionary process (called AdaW). AdaW progressively seeks a suitable distribution of weights for the given problem by elaborating several key parts in weight adaptation-weight generation, weight addition, weight deletion, and weight update frequency. Experimental results have shown the effectiveness of the proposed approach. AdaW works well for Pareto fronts with very different shapes: 1) the simplex-like, 2) the inverted simplex-like, 3) the highly nonlinear, 4) the disconnect, 5) the degenerate, 6) the scaled, and 7) the high-dimensional.
Bibliographie:ObjectType-Article-1
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ISSN:1530-9304
1530-9304
DOI:10.1162/evco_a_00269